Optimal configuration method for low-carbon building light-storage direct-current flexible energy microgrid containing phase-change material
By constructing a multi-energy coupling model and robust optimization methods, and integrating phase change thermal storage devices and photovoltaic power generation systems, the problems of uncertain photovoltaic output and high-proportion renewable energy penetration in DC microgrids are solved, thereby achieving system energy efficiency improvement and carbon emission control, which is suitable for low-carbon transformation of buildings.
Patent Information
- Application Number
- CN202511442014.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-10
- Publication Date
- 2026-02-13
AI Technical Summary
Existing technologies have room for improvement in areas such as DC microgrid architecture design, collaborative optimization of phase change thermal storage devices, and dynamic adjustment of robust parameters. They are unable to effectively address the uncertainties in photovoltaic output and the uncertainties under the penetration of high proportions of renewable energy, making it difficult to balance system economy and reliability.
This paper proposes an optimal configuration method for low-carbon building photovoltaic-storage-direct-current-flexible energy microgrids using phase change materials. Combining phase change thermal storage devices and robust optimization methods, a multi-energy coupling model is constructed to integrate photovoltaic power generation, combined heat and power, and energy storage devices. A robust optimization configuration model is established, and the GUROBI solver is used for iterative solution. The conservatism parameter is adjusted to balance economy and robustness.
It significantly reduces AC/DC conversion losses, improves energy efficiency, enhances system immunity, and reduces carbon emissions, making it suitable for microgrid planning on a practical engineering scale.
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Figure CN121529469A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of power system technology, and specifically to a method for optimizing the configuration of a low-carbon building-based photovoltaic-storage-DC-flexible energy microgrid containing phase change materials. Background Technology
[0002] As a major sector of energy consumption and carbon emissions, the building sector's low-carbon transformation is crucial for achieving carbon neutrality. Solar-storage-DC-flexible microgrid systems, integrating photovoltaic power generation, energy storage technology, and flexible loads, achieve efficient renewable energy utilization and low-carbon operation, becoming a key technological path for building decarbonization. Among these, DC distribution architecture, due to its advantages in reducing AC / DC conversion losses and improving system energy efficiency, is becoming an important development direction in microgrid design.
[0003] In scenarios with high renewable energy penetration, systems must simultaneously consider economic efficiency, reliability, and low carbon emissions, which places higher demands on planning methodologies. Current mainstream deterministic optimization methods struggle to effectively address the uncertainty of photovoltaic (PV) output, while stochastic optimization methods face the challenge of high computational complexity. To address these issues, robust optimization methods construct a reasonable uncertainty set, achieving economic optimization while ensuring system reliability, thus providing a new approach for planning PV-storage-DC-flexible microgrids.
[0004] However, existing research still has room for improvement in areas such as DC microgrid architecture design, synergistic optimization of phase change thermal energy storage devices, and dynamic adjustment of robustness parameters. Therefore, developing an optimized configuration method for photovoltaic-storage-DC-flexible microgrids based on a DC architecture to achieve synergistic optimization of system energy efficiency improvement and carbon emission control has significant practical value for promoting the low-carbon transformation of the building sector. Summary of the Invention
[0005] The purpose of this invention is to address the shortcomings of the aforementioned technologies by providing an optimized configuration method for a low-carbon building photovoltaic-storage-direct-flexible energy microgrid containing phase change materials. This method combines the advantages of phase change thermal storage devices to improve energy utilization efficiency, while also exhibiting good economic efficiency and robustness against fluctuations in photovoltaic output.
[0006] To achieve the above objectives, the present invention provides an optimized configuration method for a low-carbon building-based photovoltaic-storage-direct-drive-flexible energy microgrid containing phase change materials, comprising the following steps: S1) Establish mathematical models for photovoltaic power generation devices, combined heat and power units, electric energy storage devices, and phase change thermal energy storage devices to fully characterize the operating characteristics and energy conversion relationships of each device; S2) Combining historical data of building microgrids with the mathematical model established in step S1), a deterministic optimization configuration model is established with the goal of minimizing the sum of daily investment cost, energy procurement cost and operation and maintenance cost of the system. S3) To address the fluctuation characteristics of photovoltaic power output, an interval uncertainty set is constructed to describe its randomness. Combined with the deterministic optimization configuration model in step S2), a robust optimization configuration model incorporating the fluctuation characteristics of photovoltaic power output is established. S4) In the MATLAB environment, use the GUROBI solver to iteratively solve the robust optimization configuration model constructed in step S3). By adjusting the conservatism parameter, obtain the configuration scheme of the building microgrid under different parameters.
[0007] Preferably, in step S1), the mathematical model includes: Thermal energy storage model of phase change thermal storage device: In the formula: t At a certain moment, H ess This represents the total heat storage capacity of the phase change thermal energy storage device. Q w For storing heat in water, Q p For the heat storage of phase change materials, Q ch For heat storage in phase change thermal storage devices, Q dis For the heat release of the phase change thermal storage device, This is the maximum heat exchange limit for phase change thermal storage devices. and The maximum and minimum capacity limits for phase change thermal storage devices are specified. c w The specific heat capacity of water, c p The specific heat capacity of the phase change material. V w Let be the volume of water in the phase change thermal storage device. V p Let V be the volume of the phase change material in the phase change thermal storage device. ρ w The density of water in the phase change thermal storage device. ρ p The density of the phase change material in the phase change thermal storage device. T p The water temperature of the phase change thermal storage device. h p The phase transition enthalpy is the value per unit mass of phase change material. Water temperature model of phase change thermal storage device: In the formula: for t The water temperature of the phase change thermal storage device at any given time; Output power model of photovoltaic power generation device: In the formula: P pv The power output of the photovoltaic power generation device. η For photoelectric conversion efficiency, A The effective area of the photovoltaic power generation device. G Light intensity, β For temperature coefficient, T c This refers to the actual operating temperature of the photovoltaic power generation device. T ref For reference temperature; Model of power generation and heat generation of combined heat and power units: In the formula: P CHP For the power generation capacity of the combined heat and power unit, Q CHP The heat output of the combined heat and power unit. η e For the electrical efficiency of combined heat and power units, n h For the thermal efficiency of combined heat and power units, F gas For the gas consumption of a combined heat and power unit, Δ P max This represents the maximum ramping power of the combined heat and power unit. a max and a min These are the upper and lower limits of the heat-to-power ratio for combined heat and power (CHP) units, respectively. Capacity model of electric energy storage device: In the formula: E t For energy storage devices in t Capacity of time, η ch The charging efficiency of the energy storage device, η dis The discharge efficiency of the energy storage device. For energy storage devices at all times t The charging power, For energy storage devices at all times t The discharge power, This refers to the maximum charging power of the energy storage device. This represents the maximum discharge power of the energy storage device. E max and E minThese are the maximum and minimum capacity limits for electrical energy storage devices.
[0008] Preferably, in step S2), the deterministic optimization configuration model is: In the formula: C The daily operating cost of a microgrid, C inv The daily investment cost of a microgrid. C net For the network switching cost of microgrids, C om For the operation and maintenance costs of microgrids, C tax The carbon emission cost of microgrids; In the formula: r For the discount rate, n For the average lifespan of the equipment, P epv The rated capacity of the photovoltaic power generation device. P echp This refers to the rated capacity of the CHP unit. E eess The rated capacity of the energy storage device. E ehss This is the rated capacity of the phase change thermal storage device. C P,pv The unit power investment cost of photovoltaic power generation equipment, C P,pem The unit power investment cost of a combined heat and power (CHP) unit. C E,h2 The unit capacity investment cost of the energy storage device. E As The unit capacity investment cost of phase change material thermal storage devices; In the formula: c grid For real-time electricity prices, P grid In order to purchase electricity from the grid, c gas This is the real-time price of natural gas. F gas For natural gas purchase capacity; In the formula: P pv The power output of the photovoltaic power generation device. P CHP For the power generation capacity of the combined heat and power unit,E ess For the usable capacity of the energy storage device, E hss For the usable capacity of the phase change thermal storage device, c pv The unit power operation and maintenance cost of photovoltaic power generation devices, c chp The unit power operation and maintenance cost of combined heat and power units, c ess The unit capacity operation and maintenance cost of the energy storage device, c hss The unit capacity operation and maintenance cost of phase change thermal energy storage devices; In the formula: c tax As a carbon emission factor, P grid Power purchased from the power grid.
[0009] Preferably, in step S2), the constraints include power balance constraints on the microgrid, including photovoltaic power generation, grid power purchase, energy storage charging and discharging, and residential electricity consumption, the mathematical expression of which is shown below: In the formula: P load ( t Electricity consumption for residential use, P grid,max To limit the maximum power that can be purchased from the grid, P pv.max The maximum power limit for the power output of a photovoltaic power generation device.
[0010] Preferably, in step S2), the constraints include thermal power balance constraints on the microgrid, including residential heat load and heat storage and release of the phase change thermal storage device, the mathematical expression of which is as follows: In the formula: Q load This is the heating load for residential use.
[0011] Preferably, in step S2), the constraints include DC characteristic constraints on the microgrid, the model of which is shown below: In the formula: This is the rated voltage of the DC bus. Vdc For DC bus voltage transmission, This refers to the allowable deviation of the DC bus voltage. I sc This is the short-circuit current. Maximum permissible short-circuit current.
[0012] Preferably, in step S3), a range uncertainty set description method with adjustment capability is adopted to address the fluctuation characteristics of photovoltaic power output. Robust adjustment is achieved by using a photovoltaic power output value that does not consider uncertainty and the maximum deviation of photovoltaic power output. In the formula: Contribute to photovoltaic forecasting, It represents the maximum deviation of photovoltaic output from its nominal value.
[0013] Preferably, in step S4), the robust optimization configuration model is as follows. In the formula: For investment cost function, For the running cost function, x This is the set of capacity planning variables for each piece of equipment during the planning phase. This is the set of output variables for each device during the scheduling phase.
[0014] An electronic device includes a processor and a memory, the memory being used to store a computer program capable of running on the processor; when the processor runs the computer program, it executes the steps of a method for optimizing the configuration of a low-carbon building photovoltaic-storage-direct-flexible energy microgrid containing phase change materials.
[0015] Compared with the prior art, the present invention has the following advantages: 1. By constructing a multi-energy coupling model based on DC power distribution, integrating photovoltaic power generation, combined heat and power, electric energy storage and phase change thermal energy storage devices, the energy loss of the AC / DC conversion link in the traditional AC system is significantly reduced, and the problem of high conversion loss in the planning of traditional AC microgrids is solved. 2. By introducing a phase change thermal energy storage device, which utilizes its high energy density and temperature stability characteristics, efficient storage and precise control of thermal energy can be achieved, solving the problems of low efficiency and poor coordination of traditional thermal energy storage systems. 3. The photovoltaic power output fluctuation is described by interval uncertainty set. By adjusting the conservatism parameter, the robustness and economy of the system are dynamically balanced. Compared with traditional deterministic optimization and stochastic optimization, it can more flexibly deal with the uncertainty under the penetration of high proportion of renewable energy and improve the system's disturbance resistance. 4. Combined with the GUROBI commercial solver, it efficiently solves mixed-integer linear programming problems, improving calculation speed while ensuring optimization accuracy, and is suitable for microgrid planning on a real-world engineering scale. Attached Figure Description
[0016] Figure 1 This is a flowchart illustrating the optimized configuration method of a low-carbon building photovoltaic-storage direct-drive-flexible energy microgrid containing phase change materials according to the present invention. Figure 2 This is a framework diagram of the integrated energy system of the building microgrid in this invention; Figure 3 This is a historical data curve of the building microgrid in this invention; Figure 4 This is a typical daily power balance curve diagram in an embodiment of the present invention; Figure 5 This is a typical daily heat balance curve diagram in an embodiment of the present invention; Figure 6 This is a state diagram of a typical daily energy storage device in an embodiment of the present invention. Detailed Implementation
[0017] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0018] like Figure 1 As shown, a method for optimizing the configuration of a low-carbon building-based photovoltaic-storage-DC-flexible energy microgrid containing phase change materials includes the following steps: S1) Establish mathematical models for photovoltaic power generation devices, combined heat and power units, electric energy storage devices, and phase change thermal energy storage devices to fully characterize the operating characteristics and energy conversion relationships of each device, laying the foundation for system collaborative optimization; S2) Combining historical data of the building microgrid with the mathematical model established in step S1), the historical data includes electrical load, heat load and photovoltaic output. With the goal of minimizing the sum of the system's daily investment cost, energy procurement cost and operation and maintenance cost, constraints are established to establish a deterministic optimization configuration model. S3) To address the fluctuation characteristics of photovoltaic power output, an interval uncertainty set is constructed to describe its randomness. Combined with the deterministic optimization configuration model in step S2), a robust optimization configuration model incorporating the fluctuation characteristics of photovoltaic power output is established to enhance the system's anti-interference capability. S4) In the MATLAB environment, the robust optimization configuration model constructed in step S3) is solved iteratively using the GUROBI solver. By adjusting the conservatism parameter to balance economy and robustness, the optimal configuration scheme of the building microgrid under different parameters is obtained.
[0019] In step S1), the mathematical model includes: Phase change materials (PCMs) significantly enhance the energy density and temperature stability of thermal storage systems through their unique latent heat of phase change. During thermal storage, when the ambient temperature reaches the phase change point, the material efficiently absorbs / releases a large amount of heat energy through solid-liquid or solid-solid phase changes, while the temperature remains almost constant, thus achieving compact and long-lasting thermal energy storage. The thermal energy storage model of a phase change thermal storage device can be expressed by the following formula: In the formula: t At a certain moment, H ess This represents the total heat storage capacity of the phase change thermal energy storage device. Q w For storing heat in water, Q p For the heat storage of phase change materials, Q ch For heat storage in phase change thermal storage devices, Q dis For the heat release of the phase change thermal storage device, This is the maximum heat exchange limit for phase change thermal storage devices. and The maximum and minimum capacity limits for phase change thermal storage devices are specified. c w The specific heat capacity of water, c p The specific heat capacity of the phase change material. V w Let be the volume of water in the phase change thermal storage device. V p Let V be the volume of the phase change material in the phase change thermal storage device. ρ w The density of water in the phase change thermal storage device. ρ p The density of the phase change material in the phase change thermal storage device. T p The water temperature of the phase change thermal storage device. h p The phase transition enthalpy is the value per unit mass of phase change material. Due to its extremely high thermal resistance, phase change thermal storage devices exhibit negligible heat exchange with the environment. This characteristic enables precise temperature control and efficient thermal energy storage, making them particularly suitable for applications requiring stable heating and precise thermal management. The water temperature model for a phase change thermal storage device is as follows: In the formula: for t The water temperature of the phase change thermal storage device at any given time; Photovoltaic panels (PV panels), as the core component of photovoltaic power generation devices, directly convert solar radiation energy into electrical energy. The output power of a photovoltaic panel primarily depends on sunlight intensity and ambient temperature. The output power model of a photovoltaic power generation device is as follows: In the formula: P pv The power output of the photovoltaic power generation device. η For photoelectric conversion efficiency, A The effective area of the photovoltaic power generation device. G Light intensity, β For temperature coefficient, T c This refers to the actual operating temperature of the photovoltaic power generation device. T ref For reference temperature; Combined heat and power (CHP) units play a core role in "heat and power synergy" in building microgrid systems, simultaneously generating electricity and usable waste heat from primary energy sources. Their power generation and heat generation model is as follows: In the formula: P CHP For the power generation capacity of the combined heat and power unit, Q CHP The heat output of the combined heat and power unit. η e For the electrical efficiency of combined heat and power units, n h For the thermal efficiency of combined heat and power units, F gas For the gas consumption of a combined heat and power unit, Δ P max This represents the maximum ramping power of the combined heat and power unit. a max and a min These are the upper and lower limits of the heat-to-power ratio for combined heat and power (CHP) units, respectively. Capacity model of electric energy storage device: In the formula: E t For energy storage devices in t Capacity of time, η ch The charging efficiency of the energy storage device, η dis The discharge efficiency of the energy storage device. For energy storage devices at all times t The charging power, For energy storage devices at all times t The discharge power, This refers to the maximum charging power of the energy storage device. This represents the maximum discharge power of the energy storage device. E max and E min These are the maximum and minimum capacity limits for electrical energy storage devices.
[0020] In step S2), based on the above, a photovoltaic-storage-DC-flexible microgrid configuration model is constructed with the minimum daily operating cost of the microgrid as the optimization objective. This optimization objective consists of daily investment cost, electricity purchase cost, operation and maintenance cost, and carbon emission cost. The deterministic optimization configuration model is as follows: In the formula: C The daily operating cost of a microgrid, C inv The daily investment cost of a microgrid. C net For the network switching cost of microgrids, C om For the operation and maintenance costs of microgrids, C tax The carbon emission cost of microgrids; In the formula: r For the discount rate, n For the average lifespan of the equipment, P epv The rated capacity of the photovoltaic power generation device. P echp This refers to the rated capacity of the CHP unit. E eess The rated capacity of the energy storage device. E ehss This is the rated capacity of the phase change thermal storage device. C P,pv The unit power investment cost of photovoltaic power generation equipment, C P,pem The unit power investment cost of a combined heat and power (CHP) unit. CE,h2 The unit capacity investment cost of the energy storage device. E As The unit capacity investment cost of phase change material thermal storage devices; In the formula: c grid For real-time electricity prices, P grid In order to purchase electricity from the grid, c gas This is the real-time price of natural gas. F gas For natural gas purchase capacity; In the formula: P pv The power output of the photovoltaic power generation device. P CHP For the power generation capacity of the combined heat and power unit, E ess For the usable capacity of the energy storage device, E hss For the usable capacity of the phase change thermal storage device, c pv The unit power operation and maintenance cost of photovoltaic power generation devices, c chp The unit power operation and maintenance cost of combined heat and power units, c ess The unit capacity operation and maintenance cost of the energy storage device, c hss The unit capacity operation and maintenance cost of phase change thermal energy storage devices; In the formula: c tax As a carbon emission factor, P grid Power purchased from the power grid.
[0021] In addition, in step S2), the constraints include power balance constraints on the microgrid, including photovoltaic power generation, grid power purchase, energy storage charging and discharging, and residential electricity consumption, the mathematical expression of which is shown below: In the formula: P load ( t Electricity consumption for residential use, P grid,maxTo limit the maximum power that can be purchased from the grid, P pv.max The maximum power limit for the power output of a photovoltaic power generation device.
[0022] In addition, step S2) includes constraints on the thermal power balance of the microgrid, including residential heat load and the heat storage and release of the phase change thermal storage device, the mathematical expression of which is as follows: In the formula: Q load This is the heating load for residential use.
[0023] To ensure the voltage quality of the DC microgrid, the bus voltage deviation constraint requirement must be met. Furthermore, the DC microgrid needs to be configured with a short-circuit current suppression strategy, which can be achieved through current-limiting reactors or solid-state circuit breakers. Therefore, in step S2), the constraint conditions include DC characteristic constraints on the microgrid, the model of which is shown below: In the formula: This is the rated voltage of the DC bus. V dc For DC bus voltage transmission, This refers to the allowable deviation of the DC bus voltage. I sc This is the short-circuit current. Maximum permissible short-circuit current.
[0024] In step S3), considering the fluctuation characteristics of photovoltaic power output, an interval uncertainty set description method with adjustment capability is adopted. Robust adjustment is achieved by using the photovoltaic power output value without considering uncertainty and the maximum deviation of photovoltaic power output. In the formula: Contribute to photovoltaic forecasting, It represents the maximum deviation of photovoltaic output from its nominal value.
[0025] In step S4), after the parameters were introduced in step S3), the robust optimization configuration model is as follows. In the formula: For investment cost function, For the running cost function, x This is the set of capacity planning variables for each piece of equipment during the planning phase. This is the set of output variables for each device during the scheduling phase.
[0026] This embodiment also relates to an electronic device, including a processor and a memory, wherein the memory is used to store a computer program that can run on the processor; when the processor runs the computer program, it executes the steps of the method for optimizing the configuration of a low-carbon building photovoltaic-storage-direct-flexible energy microgrid containing phase change materials.
[0027] The technical solution of the present invention will be further explained using a photovoltaic-storage-DC-flexible energy microgrid as an example.
[0028] like Figure 2 As shown, for the constructed building microgrid, the data predictions for photovoltaic output, electrical load, and heat load in step S2) are as follows: Figure 3 The system's time-of-use electricity pricing is shown in Table 1: Table 1. Hourly Prices Simulation results: The planning scheme results are shown in Table 2: Table 2 System Planning Results Figure 4 The graph shows the power balance curve. As can be seen, the user load power remains within the range of 40-50MW with relatively small fluctuations, exhibiting a clear daily cycle. Energy storage devices primarily perform charging operations during low-load periods, while discharging during high-load periods or when renewable energy output is insufficient, demonstrating significant periodicity in their regulation behavior. Combined heat and power (CHP) units, as baseload power sources, maintain relatively stable output power, reflecting their core supporting role in the system. Photovoltaic power generation exhibits significant intermittent characteristics, heavily influenced by meteorological factors, with high output during some periods and near-zero output during others. Grid-interactive power, as a supplementary means of system power balance, complements the output of photovoltaic and energy storage units; when renewable energy output is insufficient, the grid's power purchases increase accordingly.
[0029] Figure 5 For the thermal equilibrium curve, from Figure 5 It can be seen that the building heat load demand shows a trend of first rising and then stabilizing, with the load level concentrated in the 16-28MW range. As the main heat source, the heat pump unit's output power was relatively stable in the first 15 days of operation, then significantly increased and maintained a high level in the later period, fully demonstrating its dynamic response capability to load changes. The phase change thermal storage device stores heat during periods of low heat load and when the cogeneration unit has sufficient output, and releases heat during periods of high load or when cogeneration heat supply is insufficient, effectively achieving the spatiotemporal transfer of heat energy and supply-demand balance. It is worth noting that the phase change thermal storage device undergoes a significant change in operating mode around the 16th day, shifting from primarily heat storage to primarily heat release.
[0030] Figure 6The data shows the remaining capacity changes of the battery and thermal storage tank. The capacity change of the electrochemical energy storage system exhibits stable periodic fluctuations, reflecting its conventional charge-discharge operation mode; while the phase change thermal storage device shows an operation characteristic of storing heat first and then releasing it. This difference mainly stems from the different characteristics of the electrical and thermal loads: the electrical load is relatively stable, while the thermal load shows a significant jump on day 16, prompting the thermal storage device to adjust its operating strategy. This demonstrates the differences in response characteristics among different types of energy storage systems.
[0031] The impact of the introduction of the photovoltaic-storage-direct-drive-flexible (PV-SSD) scheme on the planning results and the comparison of results from different methods are shown in Tables 3 and 4, respectively. Table 3 shows that after adopting the PV-SSD scheme, carbon emissions decreased from 798 tons to 562 tons, a reduction of 29.5%, while energy loss decreased from 8% to 5%, a reduction of 37.5%, verifying its significant advantages in energy conservation and emission reduction. Table 4 compares the performance of different optimization methods in terms of annual investment cost, total operating cost, and total cost. Deterministic optimization has the lowest total cost at 66.42 million yuan, but it does not consider uncertainty, which may lead to performance degradation in practical applications. Stochastic optimization handles uncertainty through probabilistic methods, resulting in a slightly higher total cost of 67.63 million yuan. Robust optimization, using Γ=1~9 as an example, shows that the cost increases with the value of Γ, rising from 66.96 million yuan to 68.18 million yuan, indicating that higher conservatism improves system robustness, but at the cost of increased total cost. The research results indicate that robust optimization can effectively balance economic efficiency and uncertainty, providing differentiated cost decision-making basis for different risk preferences.
[0032] Table 3 Comparison of Planning Results for Photovoltaic-Storage Direct-to-Flexible Pairing Table 4 Comparison of results with other uncertainty methods This invention presents an optimized configuration method for low-carbon building-based photovoltaic-storage-DC-flexible energy microgrids incorporating phase change materials. By constructing a multi-energy coupling model based on DC power distribution, it integrates photovoltaic power generation, combined heat and power (CHP), electrical energy storage, and phase change thermal energy storage devices. This significantly reduces energy losses in the AC / DC conversion stage of traditional AC systems, solving the problem of high conversion losses in traditional AC microgrid planning. The introduction of phase change thermal energy storage devices, utilizing their high energy density and temperature stability, enables efficient storage and precise control of thermal energy, addressing the low efficiency and poor coordination issues of traditional thermal energy storage systems. The method uses interval uncertainty sets to describe photovoltaic output fluctuations and dynamically balances system robustness and economy by adjusting the conservatism parameter. Compared to traditional deterministic and stochastic optimization, this method more flexibly addresses the uncertainties under high-proportion renewable energy penetration, improving system disturbance resistance. Combined with the GUROBI commercial solver, it efficiently solves mixed-integer linear programming problems, improving computational speed while maintaining optimization accuracy, making it suitable for microgrid planning on a practical engineering scale.
[0033] Finally, it should be noted that the above content is a further detailed description of the invention in conjunction with specific embodiments. It should not be considered that the specific implementation of the invention is limited to these descriptions. For those skilled in the art, any simple substitutions made without departing from the concept of the invention should be considered within the scope of protection of this invention. The above embodiments are merely representative examples of the invention. Obviously, the invention is not limited to the above embodiments and many variations are possible. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the invention should be considered within the scope of protection of this invention.
[0034] Furthermore, the description of the above technical solutions is exemplary, and this specification may be embodied in different forms and should not be construed as limiting it to the technical solutions set forth herein. Rather, providing these descriptions will ensure that the disclosure of this invention is thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. Moreover, the technical solutions of this invention are defined only by the scope of the claims. Features of various embodiments of the invention may be combined or spliced together in part or in whole, and may be implemented in various different configurations as will be fully understood by those skilled in the art. Embodiments of the invention may be implemented independently of each other or may be implemented together in an interdependent relationship.
[0035] For those skilled in the art, without departing from the concept of this invention, several simple deductions or substitutions can be made, and all of these should be considered to fall within the protection scope of this invention.
Claims
1. A method for optimizing the configuration of a low-carbon building-based photovoltaic-storage-DC-flexible energy microgrid containing phase change materials, characterized in that: Includes the following steps: S1) Establish mathematical models for photovoltaic power generation devices, combined heat and power units, electric energy storage devices, and phase change thermal energy storage devices to fully characterize the operating characteristics and energy conversion relationships of each device; S2) Combining historical data of building microgrids with the mathematical model established in step S1), a deterministic optimization configuration model is established with the goal of minimizing the sum of daily investment cost, energy procurement cost and operation and maintenance cost of the system. S3) To address the fluctuation characteristics of photovoltaic power output, an interval uncertainty set is constructed to describe its randomness. Combined with the deterministic optimization configuration model in step S2), a robust optimization configuration model incorporating the fluctuation characteristics of photovoltaic power output is established. S4) In the MATLAB environment, use the GUROBI solver to iteratively solve the robust optimization configuration model constructed in step S3). By adjusting the conservatism parameter, obtain the configuration scheme of the building microgrid under different parameters.
2. The method for optimizing the configuration of low-carbon building-based photovoltaic-storage-direct-drive-flexible energy microgrids containing phase change materials as described in claim 1, characterized in that: In step S1), the mathematical model includes: Thermal energy storage model of phase change thermal storage device: In the formula: t At a certain moment, H ess This represents the total heat storage capacity of the phase change thermal energy storage device. Q w For storing heat in water, Q p For the heat storage of phase change materials, Q ch For heat storage in phase change thermal storage devices, Q dis For the heat release of the phase change thermal storage device, This is the maximum heat exchange limit for phase change thermal storage devices. and The maximum and minimum capacity limits for phase change thermal storage devices are specified. c w The specific heat capacity of water, c p The specific heat capacity of the phase change material. V w Let be the volume of water in the phase change thermal storage device. V p Let V be the volume of the phase change material in the phase change thermal storage device. ρ w The density of water in the phase change thermal storage device. ρ p The density of the phase change material in the phase change thermal storage device. T p The water temperature of the phase change thermal storage device. h p The phase transition enthalpy is the value per unit mass of phase change material. Water temperature model of phase change thermal storage device: In the formula: for t The water temperature of the phase change thermal storage device at any given time; Output power model of photovoltaic power generation device: In the formula: P pv The power output of the photovoltaic power generation device. η For photoelectric conversion efficiency, A The effective area of the photovoltaic power generation device. G Light intensity, β For temperature coefficient, T c This refers to the actual operating temperature of the photovoltaic power generation device. T ref For reference temperature; Model of power generation and heat generation of combined heat and power units: In the formula: P CHP For the power generation capacity of the combined heat and power unit, Q CHP The heat output of the combined heat and power unit. η e For the electrical efficiency of combined heat and power units, n h For the thermal efficiency of combined heat and power units, F gas For the gas consumption of a combined heat and power unit, Δ P max This represents the maximum ramping power of the combined heat and power unit. a max and a min These are the upper and lower limits of the heat-to-power ratio for combined heat and power (CHP) units, respectively. Capacity model of electric energy storage device: In the formula: E t For energy storage devices in t Capacity of time, η ch The charging efficiency of the energy storage device, η dis The discharge efficiency of the energy storage device. For energy storage devices at all times t The charging power, For energy storage devices at all times t The discharge power, This refers to the maximum charging power of the energy storage device. This represents the maximum discharge power of the energy storage device. E max and E min These are the maximum and minimum capacity limits for electrical energy storage devices.
3. The method for optimizing the configuration of low-carbon building-based photovoltaic-storage-direct-drive-flexible energy microgrids containing phase change materials as described in claim 1, characterized in that: In step S2), the deterministic optimization configuration model is: In the formula: C The daily operating cost of a microgrid, C inv The daily investment cost of a microgrid. C net For the network switching cost of microgrids, C om For the operation and maintenance costs of microgrids, C tax The carbon emission cost of microgrids; In the formula: r For the discount rate, n For the average lifespan of the equipment, P epv The rated capacity of the photovoltaic power generation device. P echp This refers to the rated capacity of the CHP unit. E eess The rated capacity of the energy storage device. E ehss This is the rated capacity of the phase change thermal storage device. C P,pv The unit power investment cost of photovoltaic power generation equipment, C P,pem The unit power investment cost of a combined heat and power (CHP) unit. C E,h2 The unit capacity investment cost of the energy storage device. E As The unit capacity investment cost of phase change material thermal storage devices; In the formula: c grid For real-time electricity prices, P grid In order to purchase electricity from the grid, c gas This is the real-time price of natural gas. F gas For natural gas purchase capacity; In the formula: P pv The power output of the photovoltaic power generation device. P CHP For the power generation capacity of the combined heat and power unit, E ess For the usable capacity of the energy storage device, E hss For the usable capacity of the phase change thermal storage device, c pv The unit power operation and maintenance cost of photovoltaic power generation devices, c chp The unit power operation and maintenance cost of combined heat and power units, c ess The unit capacity operation and maintenance cost of the energy storage device, c hss The unit capacity operation and maintenance cost of phase change thermal energy storage devices; In the formula: c tax As a carbon emission factor, P grid Power purchased from the power grid.
4. The method for optimizing the configuration of low-carbon building-based photovoltaic-storage-direct-drive-flexible energy microgrids containing phase change materials as described in claim 1, characterized in that: In step S2), the constraints include power balance constraints on the microgrid, including photovoltaic power generation, grid power purchase, energy storage charging and discharging, and residential electricity consumption, the mathematical expression of which is shown below: In the formula: P load ( t Electricity consumption for residential use, P grid,max To limit the maximum power that can be purchased from the grid, P pv.max The maximum power limit for the power output of a photovoltaic power generation device.
5. The method for optimizing the configuration of low-carbon building-based photovoltaic-storage-direct-drive-flexible energy microgrids containing phase change materials as described in claim 1, characterized in that: In step S2), the constraints include thermal power balance constraints on the microgrid, including residential heat load and the heat storage and release of phase change thermal storage devices, the mathematical expression of which is as follows: In the formula: Q load This is the heating load for residential use.
6. The method for optimizing the configuration of low-carbon building-based photovoltaic-storage-direct-drive-flexible energy microgrids containing phase change materials as described in claim 1, characterized in that: In step S2), the constraints include DC characteristic constraints on the microgrid, the model of which is shown below: In the formula: This is the rated voltage of the DC bus. V dc For DC bus voltage transmission, This refers to the allowable deviation of the DC bus voltage. I sc This is the short-circuit current. Maximum permissible short-circuit current.
7. The method for optimizing the configuration of low-carbon building-based photovoltaic-storage-direct-drive-flexible energy microgrids containing phase change materials as described in claim 1, characterized in that: In step S3), robust adjustment is achieved by employing an interval uncertainty set description method with adjustment capability to address the fluctuation characteristics of photovoltaic power output. In the formula: Contribute to photovoltaic forecasting, It represents the maximum deviation of photovoltaic output from its nominal value.
8. The method for optimizing the configuration of low-carbon building-based photovoltaic-storage-direct-drive-flexible energy microgrids containing phase change materials as described in claim 1, characterized in that: In step S4), the robust optimization configuration model is as follows; In the formula: For investment cost function, For the running cost function, x This is the set of capacity planning variables for each piece of equipment during the planning phase. This is the set of output variables for each device during the scheduling phase.
9. An electronic device, characterized in that: It includes a processor and a memory, the memory being used to store a computer program that can run on the processor; when the processor runs the computer program, it executes the steps of the method for optimizing the configuration of a low-carbon building photovoltaic-storage-direct-flexible energy microgrid containing phase change materials as described in any one of claims 1 to 8.